When heart muscle tissue becomes fibrotic due to a heart attack, myocardiopathy or any other reason, it changes its electrical conducting properties. This conductivity (how diseased cells are organized in the heart, that is, the resulting topological and morphological structure of the fibrotic tissue) is important to understand arrhythmias. Having an idea of the conductivity of a patient's heart tissue in a minimally invasive way (a scan) is key to help to decide on its treatment.
Obtaining a 3D data of the heart muscle is possible using MRI, CT, echography, nuclear imaging, electroanatomical mapping, or other image acquisition technologies.
There are known some patent application in this field.
US-A1-2017178403 provides a system for computational localization of fibrillation sources. In some implementations, the system performs operations comprising generating a representation of electrical activation of a patient's heart and comparing, based on correlation, the generated representation against one or more stored representations of hearts to identify at least one matched representation of a heart. The operations can further comprise generating, based on the at least one matched representation, a computational model for the patient's heart, wherein the computational model includes an illustration of one or more fibrillation sources in the patient's heart. Additionally, the operations can comprise displaying, via a user interface, at least a portion of the computational model.
US-A1-2017068796 discloses a method and system for simulating patient-specific cardiac electrophysiology including the effect of the electrical conduction system of the heart. A patient-specific anatomical heart model is generated from cardiac image data of a patient.
The electrical conduction system of the heart of the patient is modeled by determining electrical diffusivity values of cardiac tissue based on a distance of the cardiac tissue from the endocardium. A distance field from the endocardium surface is calculated with sub-grid accuracy using a nested-level set approach. Cardiac electrophysiology for the patient is simulated using a cardiac electrophysiology model with the electrical diffusivity values determined to model the Purkinje network of the patient.
EP-A2-2672889 discloses a method of planning a patient-specific cardiac procedure including receiving three-dimensional imaging data of a patient's heart, simulating at least one of electrophysiological or electromechanical activity of at least a portion of the patient's heart using the three-dimensional imaging data, and planning the patient-specific cardiac procedure based on the simulating. The cardiac procedure is for providing a preselected alteration of at least one of electrophysiological or electromechanical behavior of the patient's heart.
EP-B1-2950270 discloses a computer implemented method for identifying channels from representative data in a 3D volume. The method comprises identifying, in a 3D volume, a zone of a first type (H) and a zone of a second type (BZ) and: automatically identifying as a candidate channel (bz) a path running through the zone of a second type (BZ) and extending between two points of the zone of a first type (H); and automatically performing, on a topological space (H_and_BZ_topo), homotopic operations between the candidate channel (bz) and paths (h) running only through the zone of a first type (H), and if the result of said homotopic operations is that the candidate channel (bz) is not homotopic to any path running only through the zone of a first type (H) identifying the candidate channel (bz) as a constrained channel.
There is a need for an automated method to obtain the structure of the fibrosis of the muscle using 3D medical images or data acquired via an acquisition technology in order to provide a basis with which to identify the arrhythmic substrate. This is useful to stratify patients according to the condition of their hearts from cardiac MRI, to decide on their treatment (for example to establish their responsiveness to an implantable defibrillator or to plan catheter ablation procedures).
Cardiac arrhythmias are caused by slow-conducting electrical circuits that use the abnormal structure of the myocardium that results from disease or infarction. The slow conduction of the electrical circuits is responsible for an electrical wave that is out of sync with the main wave responsible for the contraction of the ventricle. The asynchronous wave disrupts the healthy contraction of the myocardium, and this generates arrhythmia.
These electrical circuits join areas of healthy tissue and run through corridors within, see FIG. 1, Border-Zone (BZ) tissue (these corridors will be referred as re-entrant Conducting Channels or CC). In order for the slow wave to propagate and disrupt the main electrical activity, it needs to run through conducting tissue embedded within electrically isolating tissue. This tissue can be either scar core (dead myocytes that no longer conduct), or the wall of the endocardium and epicardium, and/or the mitral valve. The electrical isolation has to fulfill several characteristics in order to be the basis of a wave for a CC:                It needs to run for a minimum distance to allow sufficient time to have passed so that the main electrical wave has passed and the healthy myocytes are excitable again.        It needs a certain topology and morphology with a minimum amount of isolating tissue surrounding the CC. The isolating tissue can be either totally or partially covering the CC.        
CCs that are totally covered for a minimum distance are highly likely to contribute to an arrhythmogenic event. However, the ability of partially covered CCs to contribute to arrhythmogenic events depends on several morphological factors, which are analyzed in present invention.